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WNS, Part of Capgemini, Named a Leader in ISG Provider Lens® 2026 for Specialty Analytics and AI Services – Insurance

7 min Read | Sep 15, 2026

AUTHOR(s)

ISG Provider Lens Quadrant Report

WNS, part of Capgemini, has been recognized as a Leader in the ISG Provider Lens® Specialty Analytics and AI Services – Insurance 2026 report. The recognition reflects WNS' ability to combine deep insurance domain expertise with advanced analytics and AI to help insurers improve decision-making across underwriting, pricing, claims, fraud detection and customer experience.

The insurance industry is moving beyond traditional analytics and isolated AI pilots toward enterprise-scale AI transformation. As insurers contend with more complex risks, expanding data ecosystems and rising governance expectations, they are increasingly embedding predictive analytics, Gen AI and Agentic AI into insurance operations. ISG sees the market shifting from a technology-led transformation agenda toward a business-led intelligence agenda, where success is measured through outcomes such as underwriting effectiveness, claims efficiency, improved risk selection and enterprise productivity.

ISG Provider Lens 2026 Leader - Specialty Analytics and AI Services, Insurance

Why ISG Recognized WNS as a Leader in Insurance AI and Analytics Services

According to ISG, WNS delivers comprehensive insurance analytics and AI services spanning actuarial, underwriting, claims, distribution and investment functions across Property and Casualty (P&C), life and annuities, and reinsurance. Its productized approach supports scalable deployment of predictive, prescriptive and Agentic AI, while integrating diverse data sources and maintaining strong data governance and responsible AI practices.

Key strengths highlighted by ISG include:

AI-augmented underwriting and pricing using predictive and prescriptive analytics

Risk scoring, loss forecasting, price optimization and portfolio monitoring

Proprietary solutions including SKENSE and the Unified Analytics Platform for Insurance

Reusable AI components, accelerators and pre-built models tailored to insurance workflows

AI-enabled claims triage, severity prediction and fraud detection

Recovery-as-a-service capabilities supporting subrogation opportunity identification and leakage reduction

From Insurance Analytics to Enterprise-scale AI

ISG sees AI in insurance evolving from standalone analytics projects toward end-to-end transformation. Insurers are embedding analytics, Gen AI and Agentic AI into core workflows while modernizing the data foundations and governance needed to operationalize these capabilities at scale.

WNS' capabilities reflect this evolution. Its modular, insurance-specific solutions enable insurers to operationalize analytics across underwriting, claims, fraud detection and customer experience, while its broader capabilities span actuarial, distribution and investment functions. This combination of domain expertise, reusable AI components and scalable implementation helps move insurance AI transformation from individual use cases toward business workflows and measurable outcomes.

ISG Provider Lens Specialty Analytics and AI Services - Insurance 2026 quadrant, with WNS positioned as a Leader
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Analyst Perspective

“WNS Analytics demonstrates its ability to combine domain expertise with AI, regulatory alignment and explainability frameworks into pricing and underwriting workflows, enabling insurers to confidently scale AI-driven decision-making.”
Manav Deep Sachdeva & Saravanan M S

ISG

Advancing Underwriting, Claims and Risk Decisions with AI

Underwriting is one of the most significant areas of AI investment across the industry. ISG notes growing adoption of intelligent document processing, underwriting copilots, recommendation engines, predictive risk models and AI-assisted triage to augment, not replace, underwriting expertise.

WNS' AI-powered underwriting capabilities include risk scoring, loss forecasting, price optimization and portfolio monitoring, helping insurers strengthen underwriting discipline, improve pricing adequacy and align risk selection with business objectives. In claims, WNS applies AI across First Notice of Loss (FNOL), triage, severity prediction and fraud detection, complemented by recovery-as-a-service capabilities designed to improve recoveries and reduce leakage.

Download the ISG Provider Lens® Specialty Analytics and AI Services – Insurance 2026 report to explore:

01

Why WNS was recognized as a Leader

02

Key trends shaping insurance analytics and AI services

03

How insurers are scaling predictive, Gen AI and Agentic AI across the value chain

04

The growing role of AI in underwriting, pricing, claims and fraud detection

05

Why data modernization, governance and responsible AI are critical to enterprise-scale adoption

06

What insurers should look for in an insurance AI and analytics services provider

FAQs

1. What are insurance AI and analytics services?

Insurance AI and analytics services help insurers use data, predictive analytics, Gen AI, and Agentic AI to improve decision-making and automate workflows across underwriting, pricing, claims, fraud detection, risk management, customer engagement, and operations.

2. How is AI used in insurance?

Insurance leverages AI for underwriting automation, risk scoring, pricing optimization, claims triage, severity prediction, fraud detection, customer engagement, portfolio monitoring, claims recovery, and operational productivity.

3. What is agentic AI in insurance?

Agentic AI uses AI agents to perform or orchestrate multi-step insurance workflows with defined controls and human oversight. Potential applications include underwriting, claims investigation, fraud detection, customer service, and operational processes.

The ISG report specifically notes that Agentic AI can enable autonomous workflows while human oversight helps maintain trust and control.

4. How can AI improve insurance underwriting?

AI can improve underwriting by automating information gathering, analyzing structured and unstructured data, generating risk scores, forecasting losses, supporting pricing decisions, and improving portfolio monitoring.

5. How can AI improve insurance claims processing?

AI can improve claims processing through automated FNOL, claims triage, severity prediction, fraud detection, claims analysis, recovery optimization, and leakage reduction.